What is the relationship between mortality alerts and other indicators of quality of care? A national cross-sectional study

Trends in hospital admissions and mortality from diabetes mellitus in Rio Grande do Sul: historical series 2000-2020

OBJECTIVE

To analyze the trends of hospital admissions and deaths from diabetes mellitus in the 18 host municipalities of the 19 regional health coordination offices and in Rio Grande do Sul, 2000-2020.

METHOD

Ecological study with secondary data collected in the Hospital Information System, the Mortality Information System, and the Brazilian Institute of Geography and Statistics, from 2000-2020. Coefficients were standardized using the direct method and Prais-Winsten regression analysis.

RESULTS

A downward trend wasfound in the coefficients of hospitalizations for diabetes mellitus in most cities and states. In 2020, for both areas, hospitalizations for diabetes mellitus were below the average of the period. The mortality trend remained stationary in almost all municipalities and in the state.

CONCLUSION

There was evidence of a decrease in hospitalizations and stationary mortality by DM in most municipalities analyzed, possibly due to the policies and actions implemented in the period, despite the aging of the population.

Standardized mortality ratios for regionalized acute cardiovascular care

BACKGROUND

Standardized Mortality Ratios (SMRs) are case-mix adjusted mortality rates per hospital and are used to evaluate quality of care. However, acute care is increasingly organized on a regional level, with more severe patients admitted to specialized hospitals. We hypothesize that the current case-mix adjustment insufficiently captures differences in case-mix between non-specialized and specialized hospitals. We aim to improve the SMR by adding proxies of disease severity to the model and by calculating a regional SMR (RSMR) for acute cerebrovascular disease (CVD) and myocardial infarction (MI).

METHODS

We used data from the Dutch National Basic Registration of Hospital Care. We selected all admissions from 2016 to 2018. SMRs and RSMRs were calculated by dividing the observed in-hospital mortality by the expected in-hospital mortality. The expected in-hospital mortality was calculated using logistic regression with adjustment for age, sex, socioeconomic status, severity of main diagnosis, urgency of admission, Charlson comorbidity index, place of residence before admission, month/year of admission, and in-hospital mortality as outcome.

RESULTS

The IQR of hospital SMRs of CVD was 0.85-1.10, median 0.94, with higher SMRs for specialized hospitals (median 1.12, IQR 1.00-1.28, 71%-SMR > 1) than for non-specialized hospitals (median 0.92, IQR 0.82-1.07, 32%-SMR > 1). The IQR of RSMRs was 0.92-1.09, median 1.00. The IQR of hospital SMRs of MI was 0.76-1.14, median 0.98, with higher SMRs for specialized hospitals (median 1.00, IQR 0.89-1.25, 50%-SMR > 1 versus median 0.94, IQR 0.74-1.11, 44%-SMR > 1). The IQR of RSMRs was 0.90-1.08, median 1.00. Adjustment for proxies of disease severity mostly led to lower SMRs of specialized hospitals.

CONCLUSION

SMRs of acute regionally organized diseases do not only measure differences in quality of care between hospitals, but merely measure differences in case-mix between hospitals. Although the addition of proxies of disease severity improves the model to calculate SMRs, real disease severity scores would be preferred. However, such scores are not available in administrative data. As a consequence, the usefulness of the current SMR as quality indicator is very limited. RSMRs are potentially more useful, since they fit regional organization and might be a more valid representation of quality of care.

The Norton scale is an important predictor of in-hospital mortality in internal medicine patients

BACKGROUND

The Norton scale, a marker of patient frailty used to predict the risk of pressure ulcers, but the predictive value of the Norton scale for in-hospital mortality after adjustment for a wide range of demographic, and abnormal admission laboratory test results shown in themselves to have a high predictive value for in-hospital mortality is unclear.

AIM

The study aims to determine the value of the Norton scale and the presence of a urinary catheter in predicting in hospital mortality.

METHODS

The study population included all acutely admitted adult patients in 2020 through October 2021 to one of three internal medicine departments at the Laniado Hospital, a regional hospital with 400 beds in Israel. The main objective was to (a) identify the variables associated with the Norton Scale and (b) determine whether it predicts in-hospital mortality after adjustment for these variables.

RESULTS

The Norton scale was associated with an older age, female gender, presence of a urinary catheter, and abnormal laboratory tests. The odds of in-hospital mortality in those with intermediate, high, and very high Norton scale risk groups were 3.10 (2.23-3.56), 6.48 (4.02-10.46), and 12.27 (7.37-20.44), respectively, after adjustment for the remaining predictors. Adding the Norton scale and the presence of a urinary catheter to the prediction logistic regression model that included age, gender, and abnormal laboratory test results increased the c-statistic from 0.870 (0.864-0.876) to 0.908 (0.902-0.913).

CONCLUSIONS

The Norton scale and presence of a urinary catheter are important predictors of in-hospital mortality in acutely hospitalized adults in internal medicine departments.

The presence of a urinary catheter is an important predictor of in-hospital mortality in internal medicine patients

RATIONALE AND OBJECTIVE

Mortality rates are used to assess the quality of hospital care after appropriate adjustment for case-mix. Urinary catheters are frequent in hospitalized adults and might be a marker of patient frailty and illness severity. However, we know of no attempts to estimate the predictive value of indwelling catheters for specific patient outcomes. The objective of the present study was to (a) identify the variables associated with the presence of a urinary catheter and (b) determine whether it predicts in-hospital mortality after adjustment for these variables.

METHODS

The study population included all acutely admitted adult patients in 2020 (exploratory cohort) and January-October 2021 (validation cohort) to internal medicine, cardiology and intensive care departments at the Laniado Hospital, a regional hospital with 400 beds in Israel. There were no exclusion criteria. The predictor variables were the presence of a urinary catheter on admission, age, gender, comorbidities and admission laboratory test results. We used bivariate and multivariate logistic regression to test the associations between the presence of a urinary catheter and mortality after adjustment for the remaining independent variables on admission.

RESULTS

The presence of a urinary catheter was associated with other independent variables. In 2020, the odds of in-hospital mortality in patients with a urinary catheter before and after adjustment for the remaining predictors were 14.3 (11.6-17.7) and 6.05 (4.78-7.65), respectively. Adding the presence of a urinary catheter to the prediction logistic regression model increased its c-statistic from 0.887 (0.880-0.894) to 0.907 (0.901-0.913). The results of the validation cohort reduplicated those of the exploratory cohort.

CONCLUSIONS

The presence of a urinary catheter on admission is an important and independent predictor of in-hospital mortality in acutely hospitalized adults in internal medicine departments.

Association of the All-Patient Refined Diagnosis-Related Groups Severity of Illness and Risk of Mortality Classification with Outcomes

OBJECTIVES

Diagnosis-related groups (DRGs) is a patient classification system used to characterize the types of patients that the hospital manages and to compare the resources needed during hospitalization. The DRG classification is based on International Classification of Diseases diagnoses, procedures, demographics, discharge status, and complications or comorbidities and compares hospital resources and outcomes used to determine how much Medicare pays the hospital for each "product/medical condition." The All-Patient Refined DRG (APR-DRG) incorporated severity of illness (SOI) and risk of mortality (ROM) into the DRG system to adjust for patient complexity to compare resource utilization, complication rates, and lengths of stay.

METHODS

This study included 18,478 adult patients admitted to a tertiary care center in Lubbock, Texas during a 1-year period. We recorded the APR-DRG SOI and ROM and some clinical information on these patients, including age, sex, admission shock index, admission glucose and lactate levels, diagnoses based on International Classification of Diseases, Tenth Revision discharge coding, length of stay, and mortality. We compared the levels of SOI and ROM across this clinical information.

RESULTS

As the levels of SOI and ROM increase (which indicates increased disease severity and risk of mortality), age, glucose levels, lactate levels, shock index, length of stay, and mortality increased significantly (P < 0.001). Multiple logistic regression analysis demonstrated that each unit increase in ROM and SOI level was significantly associated with an 11.45 and a 10.37 times increase in the odds of in-hospital mortality, respectively. The C-statistics for the corresponding models are 0.947 and 0.929, respectively. When both ROM and SOI were included in the model, the magnitudes of increase in odds of in-hospital mortality were 5.61 and 1.17 times for ROM and SOI, respectively. The C-statistic is 0.949.

CONCLUSIONS

This study indicates that the APR-DRG SOI and ROM scores provide a classification system that is associated with mortality and correlates with other clinical variables, such as the shock index and lactate levels, which are available on admission.

A simple index predicting mortality in acutely hospitalized patients

BACKGROUND

Mortality rates used to evaluate and improve the quality of hospital care are adjusted for comorbidity and disease severity. Comorbidity, measured by International Classification of Diseases codes, do not reflect the severity of the medical condition, that requires clinical assessments not available in electronic databases, and/or laboratory data with clinically relevant ranges to permit extrapolation from one setting to the next.

AIM

To propose a simple index predicting mortality in acutely hospitalized patients.

DESIGN

Retrospective cohort study with internal and external validation.

METHODS

The study populations were all acutely admitted patients in 2015-16, and in January 2019-November 2019 to internal medicine, cardiology and intensive care departments at the Laniado Hospital in Israel, and in 2002-19, at St. James Hospital, Ireland. Predictor variables were age and admission laboratory tests. The outcome variable was in-hospital mortality. Using logistic regression of the data in the 2015-16 Israeli cohort, we derived an index that included age groups and significant laboratory data.

RESULTS

In the Israeli 2015-16 cohort, the index predicted mortality rates from 0.2% to 32.0% with a c-statistic (area under the receiver operator characteristic curve) of 0.86. In the Israeli 2019 validation cohort, the index predicted mortality rates from 0.3% to 38.9% with a c-statistic of 0.87. An abbreviated index performed similarly in the Irish 2002-19 cohort.

CONCLUSIONS

Hospital mortality can be predicted by age and selected admission laboratory data without acquiring information from the patient's medical records. This permits an inexpensive comparison of performance of hospital departments.